From ce132ab7eb6f7ec2d6dbc9c83f34518ba9160d17 Mon Sep 17 00:00:00 2001
From: diogohal <dha21@inf.ufpr.br>
Date: Tue, 28 May 2024 12:14:48 -0400
Subject: [PATCH] resultados finais teste ad
---
.../resultTop3_ad-checkpoint.csv | 17 +++
.../resultTop3_cohend-checkpoint.csv | 28 ++---
.../resultTop3_f-checkpoint.csv | 32 +++---
.../resultTop3_ks-checkpoint.csv | 22 ++--
.../resultTop3_t-checkpoint.csv | 17 +++
.ipynb_checkpoints/result_ad-checkpoint.csv | 17 +++
.../result_cohend-checkpoint.csv | 17 +++
.ipynb_checkpoints/result_f-checkpoint.csv | 17 +++
.ipynb_checkpoints/result_ks-checkpoint.csv | 26 ++---
.ipynb_checkpoints/result_t-checkpoint.csv | 17 +++
.../Normalizado/90/resultTop3_ad.csv | 17 +++
.../Normalizado/90/result_ad.csv | 17 +++
.../Normalizado/95/resultTop3_ad.csv | 17 +++
.../Normalizado/95/result_ad.csv | 17 +++
distCalc.ipynb | 105 ++++++++++++++----
15 files changed, 310 insertions(+), 73 deletions(-)
create mode 100644 .ipynb_checkpoints/resultTop3_ad-checkpoint.csv
create mode 100644 .ipynb_checkpoints/resultTop3_t-checkpoint.csv
create mode 100644 .ipynb_checkpoints/result_ad-checkpoint.csv
create mode 100644 .ipynb_checkpoints/result_cohend-checkpoint.csv
create mode 100644 .ipynb_checkpoints/result_f-checkpoint.csv
create mode 100644 .ipynb_checkpoints/result_t-checkpoint.csv
create mode 100644 Resultados_finais/Normalizado/90/resultTop3_ad.csv
create mode 100644 Resultados_finais/Normalizado/90/result_ad.csv
create mode 100644 Resultados_finais/Normalizado/95/resultTop3_ad.csv
create mode 100644 Resultados_finais/Normalizado/95/result_ad.csv
diff --git a/.ipynb_checkpoints/resultTop3_ad-checkpoint.csv b/.ipynb_checkpoints/resultTop3_ad-checkpoint.csv
new file mode 100644
index 0000000..15f6584
--- /dev/null
+++ b/.ipynb_checkpoints/resultTop3_ad-checkpoint.csv
@@ -0,0 +1,17 @@
+ano_base,match,new,empty,total
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diff --git a/.ipynb_checkpoints/resultTop3_cohend-checkpoint.csv b/.ipynb_checkpoints/resultTop3_cohend-checkpoint.csv
index 8867c2c..8d1cd07 100644
--- a/.ipynb_checkpoints/resultTop3_cohend-checkpoint.csv
+++ b/.ipynb_checkpoints/resultTop3_cohend-checkpoint.csv
@@ -1,17 +1,17 @@
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diff --git a/.ipynb_checkpoints/resultTop3_f-checkpoint.csv b/.ipynb_checkpoints/resultTop3_f-checkpoint.csv
index 902ee88..e8fbf81 100644
--- a/.ipynb_checkpoints/resultTop3_f-checkpoint.csv
+++ b/.ipynb_checkpoints/resultTop3_f-checkpoint.csv
@@ -1,17 +1,17 @@
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diff --git a/.ipynb_checkpoints/resultTop3_ks-checkpoint.csv b/.ipynb_checkpoints/resultTop3_ks-checkpoint.csv
index 5dd54b0..0aa8c4b 100644
--- a/.ipynb_checkpoints/resultTop3_ks-checkpoint.csv
+++ b/.ipynb_checkpoints/resultTop3_ks-checkpoint.csv
@@ -1,17 +1,17 @@
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diff --git a/.ipynb_checkpoints/resultTop3_t-checkpoint.csv b/.ipynb_checkpoints/resultTop3_t-checkpoint.csv
new file mode 100644
index 0000000..4e66e07
--- /dev/null
+++ b/.ipynb_checkpoints/resultTop3_t-checkpoint.csv
@@ -0,0 +1,17 @@
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diff --git a/.ipynb_checkpoints/result_ad-checkpoint.csv b/.ipynb_checkpoints/result_ad-checkpoint.csv
new file mode 100644
index 0000000..a81a212
--- /dev/null
+++ b/.ipynb_checkpoints/result_ad-checkpoint.csv
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diff --git a/.ipynb_checkpoints/result_cohend-checkpoint.csv b/.ipynb_checkpoints/result_cohend-checkpoint.csv
new file mode 100644
index 0000000..6e04a6b
--- /dev/null
+++ b/.ipynb_checkpoints/result_cohend-checkpoint.csv
@@ -0,0 +1,17 @@
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diff --git a/.ipynb_checkpoints/result_f-checkpoint.csv b/.ipynb_checkpoints/result_f-checkpoint.csv
new file mode 100644
index 0000000..e8e8ef0
--- /dev/null
+++ b/.ipynb_checkpoints/result_f-checkpoint.csv
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diff --git a/.ipynb_checkpoints/result_ks-checkpoint.csv b/.ipynb_checkpoints/result_ks-checkpoint.csv
index b1a34e9..3405fb2 100644
--- a/.ipynb_checkpoints/result_ks-checkpoint.csv
+++ b/.ipynb_checkpoints/result_ks-checkpoint.csv
@@ -1,17 +1,17 @@
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diff --git a/.ipynb_checkpoints/result_t-checkpoint.csv b/.ipynb_checkpoints/result_t-checkpoint.csv
new file mode 100644
index 0000000..709381f
--- /dev/null
+++ b/.ipynb_checkpoints/result_t-checkpoint.csv
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diff --git a/Resultados_finais/Normalizado/90/resultTop3_ad.csv b/Resultados_finais/Normalizado/90/resultTop3_ad.csv
new file mode 100644
index 0000000..ee12976
--- /dev/null
+++ b/Resultados_finais/Normalizado/90/resultTop3_ad.csv
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diff --git a/Resultados_finais/Normalizado/90/result_ad.csv b/Resultados_finais/Normalizado/90/result_ad.csv
new file mode 100644
index 0000000..505a0a4
--- /dev/null
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diff --git a/Resultados_finais/Normalizado/95/resultTop3_ad.csv b/Resultados_finais/Normalizado/95/resultTop3_ad.csv
new file mode 100644
index 0000000..15f6584
--- /dev/null
+++ b/Resultados_finais/Normalizado/95/resultTop3_ad.csv
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diff --git a/Resultados_finais/Normalizado/95/result_ad.csv b/Resultados_finais/Normalizado/95/result_ad.csv
new file mode 100644
index 0000000..a81a212
--- /dev/null
+++ b/Resultados_finais/Normalizado/95/result_ad.csv
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+2007.0,0.333,1.0,1.0,0.333
+2008.0,0.667,1.0,1.0,0.667
+2009.0,1.0,1.0,1.0,1.0
+2010.0,0.5,1.0,1.0,0.5
+2011.0,1.0,1.0,1.0,1.0
+2012.0,0.5,0.778,0.0,0.769
+2013.0,0.692,0.0,0.0,0.692
+2014.0,0.846,1.0,1.0,0.846
+2015.0,0.769,0.0,0.0,0.769
+2016.0,0.692,0.0,0.0,0.692
+2017.0,0.5,1.0,0.818,0.846
+2018.0,0.0,0.929,0.5,0.824
+2019.0,0.533,0.4,1.0,0.545
+2020.0,0.545,0.0,0.0,0.545
+2013.5,0.613,0.65,0.594,0.716
+4.031,0.253,0.439,0.461,0.183
diff --git a/distCalc.ipynb b/distCalc.ipynb
index 56599f0..5fa0194 100644
--- a/distCalc.ipynb
+++ b/distCalc.ipynb
@@ -20,7 +20,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 2,
"id": "2c81bc78-04e0-4bad-83ef-380cf3be1610",
"metadata": {
"tags": []
@@ -33,7 +33,7 @@
},
{
"cell_type": "code",
- "execution_count": 95,
+ "execution_count": 3,
"id": "af419e44-d6ef-41f7-970c-78c316aeb712",
"metadata": {
"tags": []
@@ -46,34 +46,49 @@
" self.stat_ks = []\n",
" self.stat_t = []\n",
" self.stat_cohend = []\n",
+ " self.stat_ad = []\n",
+ " \n",
" self.stat_f_matches = []\n",
" self.stat_ks_matches = []\n",
" self.stat_t_matches = []\n",
" self.stat_cohend_matches = []\n",
+ " self.stat_ad_matches = []\n",
+ " \n",
" self.stat_f_new = []\n",
" self.stat_ks_new = []\n",
" self.stat_t_new = []\n",
" self.stat_cohend_new = []\n",
+ " self.stat_ad_new = []\n",
+ " \n",
" self.stat_f_empty = []\n",
" self.stat_ks_empty = []\n",
" self.stat_t_empty = []\n",
" self.stat_cohend_empty = []\n",
+ " self.stat_ad_empty = []\n",
+ " \n",
" self.stat_f_top3 = []\n",
" self.stat_ks_top3 = []\n",
" self.stat_t_top3 = []\n",
" self.stat_cohend_top3 = []\n",
+ " self.stat_ad_top3 = []\n",
+ " \n",
" self.stat_f_matches_top3 = []\n",
" self.stat_ks_matches_top3 = []\n",
" self.stat_t_matches_top3 = []\n",
" self.stat_cohend_matches_top3 = []\n",
+ " self.stat_ad_matches_top3 = []\n",
+ " \n",
" self.stat_f_new_top3 = []\n",
" self.stat_ks_new_top3 = []\n",
" self.stat_t_new_top3 = []\n",
" self.stat_cohend_new_top3 = []\n",
+ " self.stat_ad_new_top3 = []\n",
+ " \n",
" self.stat_f_empty_top3 = []\n",
" self.stat_ks_empty_top3 = []\n",
" self.stat_t_empty_top3 = []\n",
" self.stat_cohend_empty_top3 = []\n",
+ " self.stat_ad_empty_top3 = []\n",
" self.years = []\n",
" \n",
" @property\n",
@@ -93,6 +108,10 @@
" return self.stat_cohend\n",
" \n",
" @property\n",
+ " def get_stat_ad(self):\n",
+ " return self.stat_ad\n",
+ " \n",
+ " @property\n",
" def get_stat_f_top3(self):\n",
" return self.stat_f\n",
" \n",
@@ -109,6 +128,10 @@
" return self.stat_cohend\n",
" \n",
" @property\n",
+ " def get_stat_ad_top3(self):\n",
+ " return self.stat_ad\n",
+ " \n",
+ " @property\n",
" def get_years(self):\n",
" return self.years\n",
"\n",
@@ -213,6 +236,11 @@
" self.stat_cohend_matches.append([ano, acuracia_matches])\n",
" self.stat_cohend_new.append([ano, acuracia_new_columns])\n",
" self.stat_cohend_empty.append([ano, acuracia_empty_columns])\n",
+ " elif(stat_method == 'estatistica_ad'):\n",
+ " self.stat_ad.append([ano, acuracia_total])\n",
+ " self.stat_ad_matches.append([ano, acuracia_matches])\n",
+ " self.stat_ad_new.append([ano, acuracia_new_columns])\n",
+ " self.stat_ad_empty.append([ano, acuracia_empty_columns])\n",
"\n",
"\n",
" # Calculates the three most likely new columns (Top3) to match each existing column in PDE Dataset along the years\n",
@@ -338,7 +366,12 @@
" self.stat_cohend_top3.append([ano, acuracia_total])\n",
" self.stat_cohend_matches_top3.append([ano, acuracia_matches])\n",
" self.stat_cohend_new_top3.append([ano, acuracia_new_columns])\n",
- " self.stat_cohend_empty_top3.append([ano, acuracia_empty_columns])"
+ " self.stat_cohend_empty_top3.append([ano, acuracia_empty_columns])\n",
+ " elif(stat_method == 'estatistica_ad'):\n",
+ " self.stat_ad_top3.append([ano, acuracia_total])\n",
+ " self.stat_ad_matches_top3.append([ano, acuracia_matches])\n",
+ " self.stat_ad_new_top3.append([ano, acuracia_new_columns])\n",
+ " self.stat_ad_empty_top3.append([ano, acuracia_empty_columns])"
]
},
{
@@ -351,7 +384,7 @@
},
{
"cell_type": "code",
- "execution_count": 108,
+ "execution_count": 4,
"id": "26287a6f-5537-4509-a09d-52dd59b3a76d",
"metadata": {
"tags": []
@@ -359,7 +392,7 @@
"outputs": [],
"source": [
"# Import F results\n",
- "df_f = pd.read_csv('R_resultados/Histograma_norm/F_subsequente.csv', sep=',')\n",
+ "df_f = pd.read_csv('R_resultados/Histograma_10/F_subsequente.csv', sep=',')\n",
"stat_column = 'p_valor'\n",
"df_f[stat_column] = df_f[stat_column].abs()\n",
"df_f = df_f.sort_values(by=['ano_coluna1', stat_column, 'estatistica_f'], ascending=[True, False, True])\n",
@@ -384,7 +417,14 @@
"stat_column = 'p_valor'\n",
"df_ks[stat_column] = (df_ks[stat_column]).abs()\n",
"df_ks = df_ks.sort_values(by=['ano_coluna1', stat_column, 'estatistica_ks'], ascending=[True, False, True])\n",
- "df_ks = df_ks[~df_ks['coluna1'].str.contains('ANO_CENSO') & ~df_ks['coluna2'].str.contains('ANO_CENSO')]"
+ "df_ks = df_ks[~df_ks['coluna1'].str.contains('ANO_CENSO') & ~df_ks['coluna2'].str.contains('ANO_CENSO')]\n",
+ "\n",
+ "# Import AD results\n",
+ "df_ad = pd.read_csv('R_resultados/Histograma_norm/AD_subsequente.csv', sep=',')\n",
+ "stat_column = 'p_valor'\n",
+ "df_ad[stat_column] = (df_ad[stat_column]).abs()\n",
+ "df_ad = df_ad.sort_values(by=['ano_coluna1', stat_column, 'estatistica_ad'], ascending=[True, False, True])\n",
+ "df_ad = df_ad[~df_ad['coluna1'].str.contains('ANO_CENSO') & ~df_ad['coluna2'].str.contains('ANO_CENSO')]"
]
},
{
@@ -397,7 +437,7 @@
},
{
"cell_type": "code",
- "execution_count": 109,
+ "execution_count": 8,
"id": "f9541a11-c1bf-4318-847a-100917e13204",
"metadata": {
"tags": []
@@ -405,15 +445,18 @@
"outputs": [],
"source": [
"dist = DistCalc()\n",
- "dist.calc(df_f, 'p_valor', 'estatistica_f', 0.95)\n",
- "dist.calc(df_t, 'p_valor', 'estatistica_t', 0.95)\n",
+ "dist.calc(df_f, 'p_valor', 'estatistica_f', 0.90)\n",
+ "dist.calc(df_t, 'p_valor', 'estatistica_t', 0.90)\n",
"dist.calc(df_c, 'estatistica_cohend', 'estatistica_cohend', 0.15, threshGreater=False)\n",
- "dist.calc(df_ks, 'p_valor', 'estatistica_ks', 0.95)\n",
+ "dist.calc(df_ks, 'p_valor', 'estatistica_ks', 0.90)\n",
+ "dist.calc(df_ad, 'p_valor', 'estatistica_ad', 0.90)\n",
"\n",
- "dist.calcTop3(df_f, 'p_valor', 'estatistica_f', 0.95)\n",
- "dist.calcTop3(df_t, 'p_valor', 'estatistica_t', 0.95)\n",
+ "\n",
+ "dist.calcTop3(df_f, 'p_valor', 'estatistica_f', 0.90)\n",
+ "dist.calcTop3(df_t, 'p_valor', 'estatistica_t', 0.90)\n",
"dist.calcTop3(df_c, 'estatistica_cohend', 'estatistica_cohend', 0.15, threshGreater=False)\n",
- "dist.calcTop3(df_ks, 'p_valor', 'estatistica_ks', 0.95)"
+ "dist.calcTop3(df_ks, 'p_valor', 'estatistica_ks', 0.90)\n",
+ "dist.calcTop3(df_ad, 'p_valor', 'estatistica_ad', 0.90)"
]
},
{
@@ -426,7 +469,7 @@
},
{
"cell_type": "code",
- "execution_count": 111,
+ "execution_count": 9,
"id": "527ff27d-f321-4749-a94d-dd7d824ef682",
"metadata": {
"tags": []
@@ -495,7 +538,23 @@
"resultTop3_t.loc[len(resultTop3_t)] = resultTop3_t.mean()\n",
"resultTop3_t.loc[len(resultTop3_t)] = resultTop3_t.std()\n",
"result_t = result_t.round(3)\n",
- "resultTop3_t = resultTop3_t.round(3)"
+ "resultTop3_t = resultTop3_t.round(3)\n",
+ "\n",
+ "# ================= AD =================\n",
+ "result_ad = pd.DataFrame(columns=['ano_base', 'match', 'new', 'empty', 'total'])\n",
+ "resultTop3_ad = pd.DataFrame(columns=['ano_base', 'match', 'new', 'empty', 'total'])\n",
+ "for i, ano in enumerate(dist.get_years):\n",
+ " new_row = [ano, dist.stat_ad_matches[i][1], dist.stat_ad_new[i][1], dist.stat_ad_empty[i][1], dist.stat_ad[i][1]]\n",
+ " result_ad.loc[len(result_ad)] = new_row\n",
+ " new_row = [ano, dist.stat_ad_matches_top3[i][1], dist.stat_ad_new_top3[i][1], dist.stat_ad_empty_top3[i][1], dist.stat_ad_top3[i][1]]\n",
+ " resultTop3_ad.loc[len(resultTop3_ad)] = new_row\n",
+ " \n",
+ "result_ad.loc[len(result_ad)] = result_ad.mean()\n",
+ "result_ad.loc[len(result_ad)] = result_ad.std()\n",
+ "resultTop3_ad.loc[len(resultTop3_ad)] = resultTop3_ad.mean()\n",
+ "resultTop3_ad.loc[len(resultTop3_ad)] = resultTop3_ad.std()\n",
+ "result_ad = result_ad.round(3)\n",
+ "resultTop3_ad = resultTop3_ad.round(3)"
]
},
{
@@ -508,7 +567,7 @@
},
{
"cell_type": "code",
- "execution_count": 112,
+ "execution_count": 10,
"id": "4cb4afc8-6149-40a7-8f77-af06183d4d23",
"metadata": {
"tags": []
@@ -525,7 +584,10 @@
"resultTop3_t.to_csv(f'./resultTop3_t.csv', index=False)\n",
"\n",
"result_cohend.to_csv(f'./result_cohend.csv', index=False)\n",
- "resultTop3_cohend.to_csv(f'./resultTop3_cohend.csv', index=False)"
+ "resultTop3_cohend.to_csv(f'./resultTop3_cohend.csv', index=False)\n",
+ "\n",
+ "result_ad.to_csv(f'./result_ad.csv', index=False)\n",
+ "resultTop3_ad.to_csv(f'./resultTop3_ad.csv', index=False)"
]
},
{
@@ -539,7 +601,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3 (ipykernel)",
+ "display_name": "Python 3.10.12 64-bit",
"language": "python",
"name": "python3"
},
@@ -553,7 +615,12 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.11.4"
+ "version": "3.10.12"
+ },
+ "vscode": {
+ "interpreter": {
+ "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
+ }
}
},
"nbformat": 4,
--
GitLab